Sparse Networks-Based Speedup Technique for Proteins Betweenness Centrality Computation

The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents the latest authors’ achievements regarding the analysis of the networks of proteins (interactome networks), by computing more efficiently the betweenness centrality measure. The paper introduces the concept of betweenness centrality, and then describes how betweenness computation can help the interactome network analysis. Current sequential implementations for the betweenness computation do not perform satisfactory in terms of execution times. The paper’s main contribution is centered towards introducing a speedup technique for the betweenness computation, based on modified shortest path algorithms for sparse graphs. Three optimized generic algorithms for betweenness computation are described and implemented, and their performance tested against real biological data, which is part of the IntAct dataset. Keywords—Betweenness centrality, interactome networks, proteinprotein interactions, sub-communities, sparse networks, speedup technique, IntAct.